PLM intelligence – future enterprise digital predator?

10-20 years ago enterprise software story was about data control. Who control the organizational data assets. How to access them and how to perform changes One of the most powerful data assets were related to company financial flow and resources. And it is it easy to understand – you need to control your money, otherwise you have a good chance to lose the business. No question, ERP was (and still is) the king of enterprise when it comes to controlling enterprise resources. PLM vendors were fighting their way to a corner office for a long time with mixed success. In my view, the position of PLM vendors in 2018 is much stronger than 10-15 years ago. Multiple factors influenced this change – focus on product and product services, global manufacturing, product and business competition.

The next big trend in business and manufacturing is digital transformation and you probably heard this word dozens of times or even more. In a nutshell, it is all about usage of new digital technologies for every part of the business – communication, product development, sales, etc. But almost always it comes down to one thing – data and data assets. What can make company powerful in a digital age is how company is accessing, digesting and consuming data. Most powerful digital brands in the world are all about data, data collection, processing, analysis and creating intelligence.

As much as data hits all high level of attention, in my view CAD/PLM vendors are still in pre-digital age. Majority of product data is still stored in analog form (files and legacy databases) and ability of PLM companies to process this data and produce intelligence is somewhat limited.

In my earlier article I was speaking about Big Data opportunity and PLM intelligence Data will be a key element of future paradigm shift. Ability to collect, share and communicate around data will become an essential prerequisite of future PLM intelligent applications. How to get the data? How to share right data in a company? How to get information about what product is actually customer using. All these questions are hard to answer with today PLM infrastructure and tools focusing on control of data and business processes. So, leave the process of crushing organization silos to companies and business teams. Focus on how to break data silos and deliver right data to users.

SAP’s vison for the Intelligent Digital Supply Chain. For each stage, e.g., as-designed, as-planned, as-manufactured, as-delivered, and as-operated, SAP is working with lead customers as part of their Customer Engagement Initiative. Household names like Colgate, Daimler, HP, and Steelcase help SAP define and refine their new solutions so they best meet industrial requirements. This approach is common with many of the leading PLM solution providers and CIMdata heartily agrees. It is much better to have practitioners guiding your development to help ensure the new capabilities are important and add value to enterprise processes.

An interesting part of SAP technologies is SAP data hub. I don’t have lot of sympathy to “hub” name that was used so many times in enterprise software, but the technology itself sounds fascinating.

“SAP Data Hub is the core data orchestration solution for distributed data operations in the SAP HANA Data Management Suite, our end-to-end open data framework for building modern intelligent applications that get the right data to the right users at the right time,” said Franz Faerber, executive vice president, Products & Innovation, Big Data, SAP. “Since we unveiled SAP Data Hub one year ago, customers and partners are realizing the promise of the Intelligent Enterprise by increasing data transparency, transforming data landscapes while leveraging existing investments, and building new data processes that incorporate machine learning, artificial intelligence and open source technologies.”

The following picture shows SAP’s vision of intelligence in discrete industry

And a bigger picture – intelligence everywhere in product, assets and lifecycle.

This broader product vision is necessary to support developing and deploying smart connectedproducts and to support Industry 4.0, originally Industrie 4.0 in Germany. SAP was a key playerin helping to define Industrie 4.02 and helping their lead customers reach that vision, oftenleveraging the use of smart connected products. One defining aspect of that vision is the abilityto quickly reconfigure global value chains “with App Store simplicity.”3

What is my conclusion? New skills are needed to survive in the future enterprise digital jungle. Intelligence will be a key differentiator. And there are no shortcuts in data intelligence. It is a lot of work to be done. The amount of work SAP is doing in development of holistic intelligence for product development and supply chain is impressive. Enterprise companies are turning into digital predators hunting for enterprise and product data to build a future intelligence. This is one of the main trends in future enterprise system development. I don’t see similar focus coming from pure PLM vendors. If you heard about similar initiatives developed by major PLM players, let me know. A potential risk for PLM vendors is lose the fight for intelligence enterprise. It will leave them squared into engineering business and kill PLM dream for enterprise dominance. Just my thoughts…

An interesting post was published by Luna-Tech research about the Business Process Management redefinition. Only few years ago, PLM was very focused about Collaborative Business Processes. These days I see PLM and Business Processes are not going very often together. My take is that PLM learned BPM implementation lessons. It…

A very interesting video presenting how you can track hand motion in the virtual 3D Model. The demo prepared by Robert Y. Wang and Jovan Popović. We demonstrate real-time tracking of the 3-D pose and configuration of the hand for gestural user-input and desktop virtual reality. The only components of our system…